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The role of artificial intelligence in developing humanities studies from archaeological discovery to historical recording and geographical analysis: Application models
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The Fourth Industrial Revolution represents an advanced stage of technological development, characterized by the integration of digital, physical, and biological technologies, with a strong focus on smart connectivity and advanced data analysis. At the core of this revolution stands Artificial Intelligence (AI), which enables the processing of vast amounts of data, decision-making with speed and accuracy, automation of processes, and enhancement of productivity and quality. This research examines the transformative role of AI in the humanities, particularly in archaeological, historical, and geographical studies, where traditional methods face limitations in handling complex and extensive datasets.The study aims to highlight these limitations, explore the potential of AI in analyzing diverse archaeological data to uncover new patterns, examine its role in processing large historical sources, and investigate its application in spatial data analysis for environmental and urban changes. The main hypothesis posits that AI can reveal patterns and insights unattainable by conventional methods, thereby enhancing understanding of past civilizations, historical trends, and geographical dynamics.Using a descriptive-analytical methodology supported by practical examples, the research illustrates AI applications such as satellite image analysis, artifact examination, and archival data processing. The findings indicate that integrating AI with humanities research not only improves data analysis efficiency but also maintains the critical and interpretive framework of the humanities, enabling a deeper understanding of society, history, and collective awareness in the digital era.The study concluded that integrating artificial intelligence into humanities research not only improves the efficiency and speed of data analysis but also contributes to the development of the research methodology itself, by shifting from descriptive to analytical and predictive studies, while preserving the critical and interpretive dimensions of the humanities. The study also recommends strengthening collaboration between researchers in the humanities and computer science, establishing open-source Arabic digital archives, and training researchers in the use of artificial intelligence tools. This will contribute to broadening the horizons of humanities research and connecting the past with the present within an integrated scientific framework that meets the demands of the digital age.

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Publication Date
Mon May 01 2023
Journal Name
Chemical Engineering Research And Design
Treatment of petroleum refinery wastewater by electrofenton process using a low cost porous graphite air-diffusion cathode with a novel design
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Publication Date
Thu Nov 04 2021
Journal Name
Optik - International Journal For Light And Electron Optics
Plasma parameters of Au nano-particles ablated on porous silicon produced via Nd-YAG laser at 355 nm for sensing NH3 gas
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The current study aimed the syntheses and characterizations of Gold nanoparticles (Au NPs) using a laser ablation Q-switched Nd: YAG laser with a wave-length of 355 nm at a variety of laser pulse energies (E) and deposited on porous silicon (PS). Optical emission spectrometer was used to diagnosed medium air to study gold plasma characteristics and prepared Au nanoparticles. The laser pulse energy influence has been studied on the plasma characteristics in air. The data showed the emergence of the ionic (Au II) spectral emission lines in the gold plasma emission spectrum. XRD has been utilized to examine structural characteristics. Moreover, AFM results 37.2 nm as the mean value of the diameter that is coordinated in a shape similar to the

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Improved throughput of Elliptic Curve Digital Signature Algorithm (ECDSA) processor implementation over Koblitz curve k-163 on Field Programmable Gate Array (FPGA)
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            The widespread use of the Internet of things (IoT) in different aspects of an individual’s life like banking, wireless intelligent devices and smartphones has led to new security and performance challenges under restricted resources. The Elliptic Curve Digital Signature Algorithm (ECDSA) is the most suitable choice for the environments due to the smaller size of the encryption key and changeable security related parameters. However, major performance metrics such as area, power, latency and throughput are still customisable and based on the design requirements of the device.

The present paper puts forward an enhancement for the throughput performance metric by p

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Publication Date
Mon Jan 01 2018
Journal Name
Rsc Advances
Capacitive performance of vertically aligned reduced titania nanotubes coated with Mn<sub>2</sub>O<sub>3</sub> by reverse pulse electrodeposition
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Mn2O3 was coated onto reduced titania nanotubes by reverse pulse electrodeposition, showing smooth and homogenous deposits without covering the opening of the nanotubes.

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Publication Date
Sat Jan 01 2022
Journal Name
Optik
Plasma parameters of Au nano-particles ablated on porous silicon produced via Nd-YAG laser at 355 nm for sensing NH3 gas
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a laser ablation Q-switched Nd: YAG laser with a wave-length of 355 nm at a variety of laser pulse energies (E) and deposited on porous silicon (PS). Optical emission spectrometer was used to diagnosed medium air to study gold plasma characteristics and prepared Au nanoparticles. The laser pulse energy influence has been studied on the plasma characteristics in air. The data showed the emergence of the ionic (Au II) spectral emission lines in the gold plasma emission spectrum. XRD has been utilized to examine structural characteristics. Moreover, AFM results 37.2 nm as the mean value of the diameter that is coordinated in a shape similar to the rod that appears for Au NPs, in addition to that, TEM has been an indication of the fact that syn

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Publication Date
Fri May 01 2026
Journal Name
Results In Chemistry
Advanced spectrofluorimetric determination of ascorbic acid via serotonin hydrochloride quenching using a twin solar cell device with eight-angled blue radiation sources
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novel spectrofluorimetric flow injection analysis (FIA) method was developed for the selective quantification of ascorbic acid via fluorescence quenching of serotonin hydrochloride. The system employs a custom-designed photometric array comprising 16 irradiation sources arranged in a dual-axis matrix—eight aligned horizontally and eight orthogonally, enabling multi-angle excitation and enhanced spectral resolution. Fluorescence signals were captured using a twin-pair solar cell detector, offering high sensitivity and minimal optical interference. The method exhibited a linear calibration range of 0.1–30 limit of detection (LOD) of 0.025 μ μ g/mL with a correlation coefficient (r mol /L, equivalent to 4.403 * 10 4 μ 2 ) of 0.9966, a g

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Publication Date
Wed Feb 27 2019
Journal Name
Journal Of Nano Research
A Specific NH&lt;sub&gt;3&lt;/sub&gt; Gas Sensor of a Thick MWCNTs-OH Network for Detection at Room Temperature
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NH3 gas sensor was fabricated based on deposited of Functionalized Multi-Walled Carbon Nanotubes (MWCNTs-OH) suspension on filter paper substrates using suspension filtration method. The structural, morphological and optical properties of the MWCNTs film were characterized by XRD, AFM and FTIR techniques. XRD measurement confirmed that the structure of MWCNTs is not affected by the preparation method. The AFM images reflected highly ordered network in the form of a mat. The functional groups and types of bonding have appeared in the FTIR spectra. The fingerprint (C-C stretch) of MWCNTs appears in 1365 cm-1, and the backbone of CNTs observed at 1645 cm-1. A homemade sensi

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Publication Date
Fri Jan 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
BotDetectorFW: an optimized botnet detection framework based on five features-distance measures supported by comparisons of four machine learning classifiers using CICIDS2017 dataset
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<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver &amp; kroeber, overlap, and pearson correlation

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
A Mathematical Model of a Thermally Activated Roof (TAR) Cooling System Using a Simplified RC-Thermal Model with Time Dependent Supply Water Temperature
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This paper presents a computer simulation model of a thermally activated roof (TAR) to cool a room using cool water from a wet cooling tower. Modeling was achieved using a simplified 1-D resistance-capacitance thermal network (RC model) for an infinite slab. Heat transfer from the cooling pipe network was treated as 2-D heat flow. Only a limited number of nodes were required to obtain reliable results. The use of 6th order RC-thermal model produced a set of ordinary differential equations that were solved using MATLAB - R2012a. The computer program was written to cover all possible initial conditions, material properties, TAR system geometry and hourly solar radiation. The cool water supply was considered time

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Publication Date
Thu Jun 06 2013
Journal Name
Advances In Physics Theories And Applications
Adsorption study of Symmetrical schiff base ligand 4,4 -[hydrazine -1,2- diylidenebis ( methan-1-yl-1-ylidene) bis ( 2-methoxyphenol)] on Granulated Initiated calcined Iraqi …
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